scholarly journals Human age estimation from lower-canine pulp volume ratio based on Bayes’ theorem with modern Japanese population as prior distribution

2014 ◽  
Vol 122 (1) ◽  
pp. 23-35 ◽  
Author(s):  
TOMOHIKO SASAKI ◽  
OSAMU KONDO
Keyword(s):  
Age Estimation ◽  
Prior Distribution ◽  
Japanese Population ◽  
Volume Ratio ◽  
Bayes Theorem ◽  
Lower Canine ◽  
Human Age Estimation

Bayesian Applications in Auditory Research

2019 ◽  
Vol 62 (3) ◽  
pp. 577-586 ◽  
Author(s):  
Garnett P. McMillan ◽  
John B. Cannon
Keyword(s):  
Monte Carlo ◽  
Markov Chain ◽  
Bayesian Methods ◽  
Prior Distribution ◽  
Interim Analysis ◽  
Iterative Process ◽  
Bayes Theorem ◽  
Sound Therapy ◽  
The Many ◽  
Auditory Research

Purpose This article presents a basic exploration of Bayesian inference to inform researchers unfamiliar to this type of analysis of the many advantages this readily available approach provides. Method First, we demonstrate the development of Bayes' theorem, the cornerstone of Bayesian statistics, into an iterative process of updating priors. Working with a few assumptions, including normalcy and conjugacy of prior distribution, we express how one would calculate the posterior distribution using the prior distribution and the likelihood of the parameter. Next, we move to an example in auditory research by considering the effect of sound therapy for reducing the perceived loudness of tinnitus. In this case, as well as most real-world settings, we turn to Markov chain simulations because the assumptions allowing for easy calculations no longer hold. Using Markov chain Monte Carlo methods, we can illustrate several analysis solutions given by a straightforward Bayesian approach. Conclusion Bayesian methods are widely applicable and can help scientists overcome analysis problems, including how to include existing information, run interim analysis, achieve consensus through measurement, and, most importantly, interpret results correctly. Supplemental Material https://doi.org/10.23641/asha.7822592

Complexities and considerations of human age estimation

2019 ◽  
pp. 1-15
Author(s):  
Sarah Ellingham ◽  
Joe Adserias-Garriga
Keyword(s):  
Age Estimation ◽  
Human Age Estimation

scholarly journals Correction: Accuracy of the FMF Bayes theorem-based model for predicting preeclampsia at 11–13 weeks of gestation in a Japanese population

2021 ◽  
Author(s):  
Minako Goto ◽  
Keiko Koide ◽  
Mayumi Tokunaka ◽  
Hiroko Takita ◽  
Shoko Hamada ◽  
...  
Keyword(s):  
Japanese Population ◽  
Bayes Theorem

Methods and markers used for human age estimation in forensics

2016 ◽  
Vol 294 ◽  
pp. 105-109
Author(s):  
Anna Woźniak ◽  
Keyword(s):  
Biological Material ◽  
Age Estimation ◽  
Prediction Error ◽  
Estimation Techniques ◽  
New Methods ◽  
Human Age Estimation

The article presents the previous and current methods and markers used for estimation of human age. The analysis of biological material recovered from the scene of the event makes it possible to estimate the age of a person who deposited traces. The new methods allow determining the depositor’s age, based on biological traces commonly found at the scene, such as blood, saliva or sperm, with an accuracy of a few years. The previously used age estimation techniques required larger quantities of biological material, whereas their prediction error amounted to even several decades.

Deep Learning with PCANet for Human Age Estimation

2016 ◽  
pp. 300-310 ◽  
Author(s):  
DePeng Zheng ◽  
JiXiang Du ◽  
WenTao Fan ◽  
Jing Wang ◽  
ChuanMin Zhai
Keyword(s):  
Deep Learning ◽  
Age Estimation ◽  
Human Age Estimation

Human Age Estimation Using Deep Learning from Gait Data

2021 ◽  
pp. 281-294
Author(s):  
Refat Khan Pathan ◽  
Mohammad Amaz Uddin ◽  
Nazmun Nahar ◽  
Ferdous Ara ◽  
Mohammad Shahadat Hossain ◽  
...  
Keyword(s):  
Deep Learning ◽  
Age Estimation ◽  
Human Age Estimation
Sign in / Sign up

Export Citation Format

Share Document